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Field
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collaboratively within a team. Applicants must have a PhD in materials science and engineering, chemical engineering, or related field. Excellent experimental and analytical skills relevant to the project (in
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] Subject Areas: Computational Biology / Data Analytics Machine Learning / Machine Learning Analytical Chemistry / Current Advances in Chemistry & Biochemistry Computational Science and Engineering
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related subject. A PhD (or be close to submission) in Physics, Mathematics or a related subject. Experience Experience in conducting high quality academic research. Strong publication record in peer
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analysis of data including measures of pupil dilation, microsaccades, and behavioral measures of speech perception. Experience with data collection and statistical modeling of time-series data are essential
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PhD or equivalent degree required; Significant experience in behavior testing and bioinformatic data analysis is preferred. Requires successful completion of a background check. Selected candidate may
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. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
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and in vivo experiments and generating single-cell sequencing data Analyzing recorder outputs and high-dimensional datasets to study cancer evolution Presenting and preparing results for publication
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. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
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data collection approaches. Familiarity with or strong motivation to learn machine learning or advanced data analytics for pattern detection and forecasting in environmental data. Familiarity with
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responsibilities will include working within clinical researchers associated with the project, taking responsibility for completion of data analysis, and helping with the supervision of PhD students working